Network-based features enable prediction of essential genes across diverse organisms.

ABSTRACT: Machine learning approaches to predict essential genes have gained a lot of traction in recent years. These approaches predominantly make use of sequence and network-based features to predict essential genes. However, the scope of network-based features used by the existing approaches is very narrow. Further, many of these studies focus on predicting essential genes within the same organism, which cannot be readily used to predict essential genes across organisms. Therefore, there is clearly a need for a method that is able to predict essential genes across organisms, by leveraging network-based features. In this study, we extract several sets of network-based features from protein-protein association networks available from the STRING database. Our network features include some common mea

SUBMITTER: Azhagesan K 

PROVIDER: S-EPMC6292609 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature